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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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Volume 14, issue 21 | Copyright
Atmos. Chem. Phys., 14, 11791-11815, 2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 11 Nov 2014

Research article | 11 Nov 2014

De praeceptis ferendis: good practice in multi-model ensembles

I. Kioutsioukis1,2 and S. Galmarini1 I. Kioutsioukis and S. Galmarini
  • 1European Commission, Joint Research Center, Institute for Environment and Sustainability, Ispra (VA), Italy
  • 2Laboratory of Atmospheric Physics, Physics Department, University of Patras, Greece

Abstract. Ensembles of air quality models have been formally and empirically shown to outperform single models in many cases. Evidence suggests that ensemble error is reduced when the members form a diverse and accurate ensemble. Diversity and accuracy are hence two factors that should be taken care of while designing ensembles in order for them to provide better predictions. Theoretical aspects like the bias–variance–covariance decomposition and the accuracy–diversity decomposition are linked together and support the importance of creating ensemble that incorporates both these elements. Hence, the common practice of unconditional averaging of models without prior manipulation limits the advantages of ensemble averaging. We demonstrate the importance of ensemble accuracy and diversity through an inter-comparison of ensemble products for which a sound mathematical framework exists, and provide specific recommendations for model selection and weighting for multi-model ensembles. The sophisticated ensemble averaging techniques, following proper training, were shown to have higher skill across all distribution bins compared to solely ensemble averaging forecasts.

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